With increasing popularity in high-speed machining due to its high efficiency, there is a vital need for more accurate prediction of dynamic behaviors for high-speed motorized spindles. The spindle units integrate tools with built-in motors hence a comprehensive model is required to include the multi-physics coupling property. This article presents an integrated model which consists of four coupled sub-models: state, shaft, bearing, and thermal model. Using the variational principle, a state model for the motor-spindle system is generated, which can describe the running state of the spindle, and provide electrical parameters to study the motor heat generation for thermal model and the unbalanced magnetic force for shaft dynamic model. The thermal model is coupled with the bearing and shaft dynamic model through bearing heat generation and thermal displacement. Thus, the entire model becomes an integrated electro-thermomechanical dynamic model. The proposed integrated model is investigated by a solution procedure and validated experimentally, and it shows that the model is capable of accurately predicting the dynamic behaviors of motorized spindles. The coupling relationship among the electrical, thermal, and mechanical behaviors of the system becomes clear from the simulation and experimental results, and some feasible methods to improve the dynamic performances of the system are obtained.
An adaptive directional cubic convolution interpolation method for integrated circuit (IC) chip defect images is proposed in this paper, to meet the challenge of preserving edge and texture information. In the proposed method, Otsu thresholding technique is employed to distinguish strong edge pixels from weak ones and texture regions, and estimate the direction of strong edges, adaptively. Boundary pixels are pre-interpolated using the original bicubic interpolation method to help improve the interpolation accuracy of the interior pixels. The experimental results of both classic test images and IC chip defect images demonstrate that the proposed method outperforms the competing methods with better edge and texture preservation, interpolation quality, more natural visual effect of the interpolated images and reasonable computational time. The proposed method can provide high quality IC chip images for defect detection and has been successfully applied on practical vision inspection for IC chips
A hybrid drive and control technique is proposed for high-speed motorized spindle system. The proposed control technique enjoys the advantages of vector control and direct torque control and avoids the implementation difficulties of the two control methods. In particular, the control system includes an optimized switching table based on adaptive fuzzy neural network control which can prevent the system from the high level of torque ripple and nonsinusoidal current waveforms. A simulation model of the spindle's hybrid drive and control system is constructed in MATLAB/Simulink, and then the related experiments are carried out on a high-speed motorized spindle whose rated speed is 15,000 r/min. The simulation and experimental results reveal that the proposed model and technique are correct and the model has excellent dynamic and static performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.